Instructions to use falgasdev/zitfac1al with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use falgasdev/zitfac1al with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Tongyi-MAI/Z-Image-Turbo", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("falgasdev/zitfac1al") prompt = "-" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
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Download README.md from falgasdev/zitfac1al: direct link, hf CLI and curl.
- Browser
- Download file 357 Bytes
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https://huggingface.co/falgasdev/zitfac1al/resolve/main/README.md
- Command line
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hf download hf://falgasdev/zitfac1al/README.md
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curl -L -o README.md https://huggingface.co/falgasdev/zitfac1al/resolve/main/README.md
357 Bytes
| tags: | |
| - text-to-image | |
| - lora | |
| - diffusers | |
| - template:diffusion-lora | |
| widget: | |
| - output: | |
| url: images/fire-letter-z-your-design-50682304.webp | |
| text: '-' | |
| base_model: Tongyi-MAI/Z-Image-Turbo | |
| instance_prompt: null | |
| # zimagefac1al | |
| <Gallery /> | |
| ## Download model | |
| [Download](/falgasdev/zitfac1al/tree/main) them in the Files & versions tab. | |